Search results for: basal reinforcement

Authors: B. Z. Manuel, H. D. Esmeralda, H. S. Felipe, D. R. Héctor, D. de la Torre Sebastián, R. L. Diego

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Aluminum Matrix Composites reinforced with nanocrystalline Ni3Al carbon-coated intermetallic particles, were synthesized by powder metallurgy. Powder mixture of aluminum with 0.5-volume fraction of reinforcement particles was compacted by spark plasma sintering (SPS) technique and the compared with conventional sintering process. The better results for SPS technique were obtained in 520ºC-5kN-3min.The hardness (70.5±8 HV) and the elastic modulus (95 GPa) were evaluated in function of sintering conditions for SPS technique; it was found that the incorporation of these kind of reinforcement particles in aluminum matrix improve its mechanical properties. The densities were about 94% and 97% of the theoretical density. The carbon coating avoided the interfacial reaction between matrix-particle at high temperature (520°C) without show composition change either intermetallic dissolution.

Keywords: aluminum matrix composites, intermetallics, spark plasma sintering, nanocrystalline

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Authors: M. Linek, P. Nita

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In the previous airfield construction industry, pavements made of reinforced concrete have been used very rarely; however, the necessity to use this type of pavements in an emergency situations justifies the need reference to this issue. The paper concerns the problem of airfield pavement dimensioning made of reinforced concrete and the evaluation of selected dimensioning methods of reinforced concrete slabs intended for airfield pavements. Analysis of slabs dimensioning, according to classical method of limit states has been performed and it has been compared to results obtained in case of methods complying with Eurocode 2 guidelines. Basis of an analysis was a concrete slab of class C35/45 with reinforcement, located in tension zone. Steel bars of 16.0 mm have been used as slab reinforcement. According to comparative analysis of obtained results, conclusions were reached regarding application legitimacy of the discussed methods and their design advantages.

Keywords: rainforced concrete, cement concrete, airport pavements, dimensioning

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Authors: Hooman Dabirmanesh, Attila M. Zsaki

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The toppling failure mode in a rock mass is considerably different from the most common sliding failure type along an existing or an induced slip plane. Block toppling is observed in a rock mass which consists of both a widely-spaced basal cross-joint set and a closely-spaced discontinuity set dipping into the slope. For this case, failure occurs when the structure cannot bear the tensile portion of bending stress, and the columns or blocks overturn by their own weight. This paper presents a particle-based discrete element model of rock blocks subjected to a toppling failure where geometric conditions and interaction among blocks are investigated. A series of parametric studies have been conducted on particles’ size, arrangement and bond contact among of particles which are made the blocks. Firstly, a numerical investigation on a one-block system was verified. Afterward, a slope consisting of multi-blocks was developed to study toppling failure and interaction forces between blocks. The results show that the formation of blocks, especially between the block and basal plane surface, can change the process of failure. The results also demonstrate that the initial configuration of particles used to form the blocks has a significant role in achieving accurate simulation results. The size of particles and bond contacts have a considerable influence to change the progress of toppling failure.

Keywords: block toppling failure, contact interaction, discrete element, particle size, random generation

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Dipanshu Sur, Ratnabali Chakravorty

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Background: Striae result from rapid expansion of the underlying tissue, e.g. during puberty, pregnancy or rapid weight gain. Prior data indicate that the incidence of stretch marks in Indian women is 77%.The hormonal and genetic factors are associated with their appearance. Recently that has been found skin extensibility, elasticity and rupture were strongly influenced by the water content of dermis and epidermis cells. Objective: The objectives were to assess the effects of topical treatments applied during pregnancy on the later development of stretch marks. Materials and methods: An open, prospective, randomized study was done on 120 pregnant women in whom skin elasticity and hydration as well as striae presence or apparition were measured at baseline and periodically until delivery. Patients were randomly assigned to application in wet skin cream, or in dry skin conditions. Results: The average basal hydration was 42 ±13 IU and the final was 46 ± 6 IU (P = 0.0325; 95% CI: -7.66 to -0.34), which difference was statistically significant. By measuring the moisture in the control region (forearm) a basal reading of 40 ± 9 IU and end of study of 38 ± 6; (p = 0.1547; 95% CI: -0.77 to 4.77) and this difference was considered to be not statistically significant. It was observed that at the end of the study, 55% women without ridges; mild ridges 5%; 36% moderate, and 4%, severe ridges. The proportion of women without grooves was 54% when the cream was applied studied wet skin and 45% when the cream was applied on dry skin. Conclusion: It was shown that cream under study increased hydration and elasticity of abdominal skin consequently in all subjects. This effect is more significant (54%) when the cream is applied to damp skin.

Keywords: striae gravidarum, skin moisturizer, skin hydration, skin elasticity

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Authors: A. Bouhaloufa, T. Kadri, S. Zouaoui, A. Belhacene

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To put more durable bridges, it is important to maintain existing structures, rather than investing in new structures. Instead of demolishing the old bridge and replace them with new, we must preserve and upgrade using better methods of diagnosis, auscultation and repair, the interest of this work is to increase the bearing capacity bridges damaged by additional prestressing, this type of reinforcement is growing continuously. In addition to excellent static strength, prestressing also has a very high resistance to fatigue, so it is suitable to solve the problem of failure of the bearing capacity of the bridges. This failure often comes to the development of overloads in quantity and quality, that is our daily traffic has increased and become very complicated, on the other hand its constituents are advanced in weight and speed and therefore almost all old bridges became unable to support the movement of the latter and remain disabled to all these problems. The main purpose of this work includes the following three aspects: - Determination of the main diseases and factors affecting the deterioration of bridges in Algeria, - Evaluation of the bearing capacity of bridges, - Proposal technical reinforcement to improve the bearing capacity of a degraded structure.

Keywords: bridges, repair, auscultation, diagnosis, pathology, additional prestressing

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Authors: Ki-Seok Kwon, Heung-Youl Kim

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This research evaluated fire resistances of high-strengthened reinforced concrete (RC) column, spiral wire rope which applied with 60, and 100MPa. The fire resistance test of RC column with loading condition was conducted following the ISO 834 (3 hours). This experiment set mixing of fiber (PP fiber, Steel fiber) and types of horizontal reinforcement as a variable of reinforcement method. The fire resistance test measured the main steel bar’s max and mean temperatures also the shrinkage and shrinking ratio of columns(500 X 500 X 3,000mm) with loadings. As a result, the specimen of 60MPa attained three hours fire resistance with only spiral wire rope. Also, the specimen of 100MPa must be reinforced with fibers and spiral wire rope to attain three hours fire resistance.

Keywords: reinforced concrete column, high strength concrete, wire rope, fire resistance test

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Authors: Tanyaporn Chairoch

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Introduction: Cannabis is a drug to treat patients with many diseases such as Multiple sclerosis, Alzheimer’s disease, and Epilepsy, where theycontain many active compounds such as delta-9 tetrahydrocannabinol (THC) and cannabidiol (CBD). Especially, THC is the primary psychoactive ingredient in cannabis and binds to cannabinoid 1 (CB1) receptors. Moreover, CB1 is located on the neocortex, hippocampus, basal ganglia, cerebellum, and brainstem. In previous study, we found the association between the variant of CB1recptors gene (rs2023239) and decreased effect of nicotine reinforcement in patients. However, there are no data describing whether the distribution of CB1 receptor gene is a genetic marker for Thai patients who are treated with cannabis. Objective: Thus, the aim of this study we want to investigate the frequency of the CB1 receptor gene in Thai patients. Materials and Methods: All of sixty Thai patients received the medical cannabis for treatment who were recruited in this study. DNA will be extracted from EDTA whole blood by Genomic DNA Mini Kit. The genotyping of CNR1 gene (rs 2023239) was genotyped by the TaqMan real time PCR assay (ABI, Foster City, CA, USA).and using the real-time PCR ViiA7 (ABI, Foster City, CA, USA). Results: We found thirty-eight (63.3%) Thai patients were female, and twenty-two (36.70%) were male in this study with median age of 45.8 (range19 – 87 ) years. Especially, thirty-two (53.30%) medical cannabis tolerant controls were female ( 55%) and median age of52.1 (range 27 – 79 ) years. The most adverse effects for medical cannabis treatment was tachycardia. Furthermore, the number of rs 2023239 (TT) carriers was 26 of 27 (96.29%) in medical cannabis-induced adverse effects and 32 of 33 (96.96%) in tolerant controls. Additionally, rs 2023239 (CT) variant was found just only one of twenty-seven (3.7%) in medical cannabis-induced adverse effects and 1 of 33 (3.03%) in tolerant controls. Conclusions: The distribution of genetic variant in CNR1 gene might serve as a pharmacogenetics markers for screening before initiating the therapy with medical cannabis in Thai patients.

Keywords: cannabis, pharmacogenetics, CNR1 gene, thai patient

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Authors: Metwally Abdel Aziz Ahmed, Ahmed Shaban Abdel Hay Gabr, Inas Mohamed Saleh

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The main objective of structural design is to ensure safety and functional performance requirements of a structural system for its target reliability levels. In this study, the reliability index for the reinforcement concrete slender columns with rectangular cross section is studied. The variable parameters studied include the loads, the concrete compressive strength, the steel yield strength, the dimensions of concrete cross-section, the reinforcement ratio, and the location of steel placement. Risk analysis program was used to perform the analytical study. The effect of load eccentricity on the reliability index of reinforced concrete slender column was studied and presented. The results of this study indicate that the good quality control improve the performance of slender reinforced columns through increasing the reliability index β.

Keywords: reliability, reinforced concrete, safety, slender column

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Authors: Orkide Donma, Mustafa M. Donma

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Basal metabolic rate (BMR) is widely used and an accepted measure of energy expenditure. Its principal determinant is body mass. However, this parameter is also correlated with a variety of other factors. The objective of this study is to measure BMR and compare it with the values obtained from predictive equations in adults classified according to their body mass index (BMI) values. 276 adults were included into the scope of this study. Their age, height and weight values were recorded. Five groups were designed based on their BMI values. First group (n = 85) was composed of individuals with BMI values varying between 18.5 and 24.9 kg/m². Those with BMI values varying from 25.0 to 29.9 kg/m² constituted Group 2 (n = 90). Individuals with 30.0-34.9 kg/m², 35.0-39.9 kg/m², > 40.0 kg/m² were included in Group 3 (n = 53), 4 (n = 28) and 5 (n = 20), respectively. The most commonly used equations to be compared with the measured BMR values were selected. For this purpose, the values were calculated by the use of four equations to predict BMR values, by name, introduced by Food and Agriculture Organization (FAO)/World Health Organization (WHO)/United Nations University (UNU), Harris and Benedict, Owen and Mifflin. Descriptive statistics, ANOVA, post-Hoc Tukey and Pearson’s correlation tests were performed by a statistical program designed for Windows (SPSS, version 16.0). p values smaller than 0.05 were accepted as statistically significant. Mean ± SD of groups 1, 2, 3, 4 and 5 for measured BMR in kcal were 1440.3 ± 210.0, 1618.8 ± 268.6, 1741.1 ± 345.2, 1853.1 ± 351.2 and 2028.0 ± 412.1, respectively. Upon evaluation of the comparison of means among groups, differences were highly significant between Group 1 and each of the remaining four groups. The values were increasing from Group 2 to Group 5. However, differences between Group 2 and Group 3, Group 3 and Group 4, Group 4 and Group 5 were not statistically significant. These insignificances were lost in predictive equations proposed by Harris and Benedict, FAO/WHO/UNU and Owen. For Mifflin, the insignificance was limited only to Group 4 and Group 5. Upon evaluation of the correlations of measured BMR and the estimated values computed from prediction equations, the lowest correlations between measured BMR and estimated BMR values were observed among the individuals within normal BMI range. The highest correlations were detected in individuals with BMI values varying between 30.0 and 34.9 kg/m². Correlations between measured BMR values and BMR values calculated by FAO/WHO/UNU as well as Owen were the same and the highest. In all groups, the highest correlations were observed between BMR values calculated from Mifflin and Harris and Benedict equations using age as an additional parameter. In conclusion, the unique resemblance of the FAO/WHO/UNU and Owen equations were pointed out. However, mean values obtained from FAO/WHO/UNU were much closer to the measured BMR values. Besides, the highest correlations were found between BMR calculated from FAO/WHO/UNU and measured BMR. These findings suggested that FAO/WHO/UNU was the most reliable equation, which may be used in conditions when the measured BMR values are not available.

Keywords: adult, basal metabolic rate, fao/who/unu, obesity, prediction equations

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Authors: Uche C. Okafor, Nwanneka M. Okpokwu, Felix Nwafor, Carl E. A. Okezie

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Securidaca longepedunculata Fresen (Violet tree) belongs to the family Polygalaceae characterised by papillionaceous purplish flowers. This medicinally valued plant disappears at an alarming rate due to intensified anthropopressure particularly the unregulated manner of subterranean plant parts' collection from natural stands. Some indiscriminately harvested plants bear seeds containing both mature and immature zygotic embryos that are often discarded. Here, such seeds are collected for this experiment. Seeds were collected, washed, de-coated, and dipped in 70 % (v/v) ethanol for 30 s followed by rising in 5 % solution sodium hypochlorite, containing two drops of tween 20, for another 25 min. Mature zygotic embryos (MZEs) were excised from seeds and cultured in two basal media (MS and B5), three carbon sources (sucrose, glucose and fructose) at five concentrations (0-40 g/L) while immature zygotic embryos (iMZEs) were composed on similar basal media and carbon source supplemented with 0-2 mg/L Benzylaminopurine (BAP) and 0-2 mg/L Indole acetic acid (IAA). MZEs cultured on MS + 30g/L sucrose differed significantly from other treatments at p≤0.05 with maximum percent sprouting (85.24± 5.67 %) and shoot length (7.53±0.67 cm). MZEs culture had the maximum percent sprouting (85.24± 5.67 %) and shoot length (7.53±0.67 cm) in medium containing MS+ 30g L-1 sucrose. iMZEs on the other hand had maximum growth on MS + 40g/L sucrose supplemented with 1.5 mg/L IAA+ 1.0 mg/L BAP. This study is a geared towards creating an alternative path for the maximum production of plants in vitro, thereby, preventing the plants from disappearing.

Keywords: Gamborg's medium, Murashige and Skoog medium, Securidaca longepedunculata, zygotic embryos

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Authors: Vivian A. Galindo, Maria C. Galvis, Jaime R. Obando, Alvaro Guarin

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In Colombia, most of the roads of the national tertiary road network are unpaved roads with granular rolling surface. These are very important ways of guaranteeing the mobility of people, products, and inputs from the agricultural sector from the most remote areas to urban centers; however, it has not paid much attention to the search for alternatives to avoid the occurrence of deteriorations that occur shortly after its commissioning. In recent years, geosynthetics have been used satisfactorily to reinforce unpaved roads on soft soils, with geotextiles and geogrids being the most widely used. The interaction of the geogrid and the aggregate minimizes the lateral movement of the aggregate particles and increases the load capacity of the material, which leads to a better distribution of the vertical stresses, consequently reducing the vertical deformations in the subgrade. Taking into account the above, the research aimed at the mechanical behavior of the granular material, used in unpaved roads with and without the presence of geogrids, from the development of laboratory tests through the loaded wheel tester (LWT). For comparison purposes, the reinforced conditions and traffic conditions to which this type of material can be accessed in practice were simulated. In total four types of geogrids, were tested with granular material; this means that five test sets, the reinforced material and the non-reinforced control sample were evaluated. The results of the numbers of load cycles and depth rutting supported by each test body showed the influence of the properties of the reinforcement on the mechanical behavior of the assembly and the significant increases in the number of load cycles of the reinforced specimens in relation to those without reinforcement.

Keywords: geosynthetics, load wheel tester LWT, tertiary roads, unpaved road, vertical deformation

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Authors: Masato Nishi, Tetsushi Kaburagi, Masashi Kurose, Tei Hirashima, Tetsusei Kurasiki

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The process of thermoforming a carbon fiber reinforced thermoplastic (CFRTP) has increased its presence in the automotive industry for its wide applicability to the mass production car. A non-isothermal forming for CFRTP can shorten its cycle time to less than 1 minute. In this paper, the textile reinforcement FE model which the authors proposed in a previous work is extended to the CFRTP model for non-isothermal forming simulation. The effect of thermoplastic is given by adding shell elements which consider thermal effect to the textile reinforcement model. By applying Reuss model to the stress calculation of thermoplastic, the proposed model can accurately predict in-plane shear behavior, which is the key deformation mode during forming, in the range of the process temperature. Using the proposed model, thermoforming simulation was conducted and the results are in good agreement with the experimental results.

Keywords: carbon fiber reinforced thermoplastic, finite element analysis, pre-impregnated textile composite, non-isothermal forming

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Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

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Authors: Mohammad Reza Koushki Ardestani, Saeed Daneshmand, Mohammad Heydari Vini

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In the present study, AA7075/SiO2 composites have been fabricated via liquid metallurgy process. Using the degassing process, the wet ability of the molten aluminum alloys increased which improved the bonding between aluminum matrix and reinforcement (SiO2) particles. AA7075 alloy and SiO2 particles were taken as the base matrix and reinforcements, respectively. Then, contents of 2.5 and 5 wt. % of SiO2 subdivisions were added into the AA7075 matrix. To improve wettability and distribution, reinforcement particles were pre-heated to a temperature of 550°C for each composite sample. A uniform distribution of SiO2 particles was observed through the matrix alloy in the microstructural study. A hardened EN32 steel disc as the counter face was used to evaluate the wear rate pin-on-disc, a wear testing machine containing. The results showed that the wear rate of the AA/SiO2 composites was lesser than that of the monolithic AA7075 samples. Finally, The SEM worn surfaces of samples were investigated.

Keywords: Al7075, SiO₂, wear, composites, stir casting

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Authors: Parisa Ahmadi Oliaei, Seyed Abolhassan Naeini

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The knowledge of soil–reinforcement interaction parameters is particularly important in the design of reinforced soil structures. The pull-out test is one of the most widely used tests in this regard. The results of tensile tests may be very sensitive to boundary conditions, and more research is needed for a better understanding of the Pull-out response of reinforcement, so numerical analysis using the finite element method can be a useful tool for the understanding of the Pull-out response of soil-geogrid interaction. The main objective of the present study is to compare the numerical and experimental results of Pull- out a test on geogrid-reinforced sandy soils interactions. Plaxis 2D finite element software is used for simulation. In the present study, the pull-out test modeling has been done on sandy soil. The effect of geogrid hardness was also investigated by considering two different types of geogrids. The numerical results curve had a good agreement with the pull-out laboratory results.

Keywords: plaxis, pull-out test, sand, soil- geogrid interaction

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Authors: Ziying Wu, Danfeng Yan

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Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.

Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network

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Authors: Marcelo Sanhueza Cartes, Nelson Maureira Carsalade

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This research evaluates the effectiveness of a pallet isolation device for the protection of selective-type industrial storage racks. The device works only in the longitudinal direction of the aisle, and it is made up of a platform installed on the rack beams. At both ends, the platform is connected to the rack structure by means of a spring-damper system working in parallel. A system of wheels is arranged between the isolation platform and the rack beams in order to reduce friction, decoupling of the movement and improve the effectiveness of the device. The latter is evaluated by the reduction of the maximum dynamic responses of basal shear load and story drift in relation to those corresponding to the same rack with the traditional construction system. In the first stage, numerical simulations of industrial storage racks were carried out with and without the pallet isolation device. The numerical results allowed us to identify the archetypes in which it would be more appropriate to carry out experimental tests, thus limiting the number of trials. In the second stage, experimental tests were carried out on a shaking table to a select group of full-scale racks with and without the proposed device. The movement simulated by the shaking table was based on the Mw 8.8 magnitude earthquake of February 27, 2010, in Chile, registered at the San Pedro de la Paz station. The peak ground acceleration (PGA) was scaled in the frequency domain to fit its response spectrum with the design spectrum of NCh433. The experimental setup contemplates the installation of sensors to measure relative displacement and absolute acceleration. The movement of the shaking table with respect to the ground, the inter-story drift of the rack and the pallets with respect to the rack structure were recorded. Accelerometers redundantly measured all of the above in order to corroborate measurements and adequately capture low and high-frequency vibrations, whereas displacement and acceleration sensors are respectively more reliable. The numerical and experimental results allowed us to identify that the pallet isolation period is the variable with the greatest influence on the dynamic responses considered. It was also possible to identify that the proposed device significantly reduces both the basal cut and the maximum inter-story drift by up to one order of magnitude.

Keywords: pallet isolation system, industrial storage racks, basal shear load, interstory drift.

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Authors: Alica Höpken, Hergen Pargmann

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The resource-efficient planning of the complex production planning processes in the meat industry and the reduction of food waste is a permanent challenge. The complexity of the production planning process occurs in every part of the supply chain, from agriculture to the end consumer. It arises from long and uncertain planning phases. Uncertainties such as stochastic yields, fluctuations in demand, and resource variability are part of this process. In the meat industry, waste mainly relates to incorrect storage, technical causes in production, or overproduction. The high amount of food waste along the complex supply chain in the meat industry could not be reduced by simple solutions until now. Therefore, resource-efficient production planning by conventional methods is currently only partially feasible. The realization of intelligent, automated production planning is basically possible through the application of machine learning algorithms, such as those of reinforcement learning. By applying the adapted design thinking method, machine learning methods (especially reinforcement learning algorithms) are used for the complex production planning process in the meat industry. This method represents a concretization to the application area. A resource-efficient production planning process is made available by adapting the design thinking method. In addition, the complex processes can be planned efficiently by using this method, since this standardized approach offers new possibilities in order to challenge the complexity and the high time consumption. It represents a tool to support the efficient production planning in the meat industry. This paper shows an elegant adaption of the design thinking method to apply the reinforcement learning method for a resource-efficient production planning process in the meat industry. Following, the steps that are necessary to introduce machine learning algorithms into the production planning of the food industry are determined. This is achieved based on a case study which is part of the research project ”REIF - Resource Efficient, Economic and Intelligent Food Chain” supported by the German Federal Ministry for Economic Affairs and Climate Action of Germany and the German Aerospace Center. Through this structured approach, significantly better planning results are achieved, which would be too complex or very time consuming using conventional methods.

Keywords: change management, design thinking method, machine learning, meat industry, reinforcement learning, resource-efficient production planning

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Authors: Vara Prasad Vemu

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The aim of the present work is to investigate the mechanical properties and water absorption capacity of carbon and basalt fibers mixed with matrix epoxy. At present, there is demand for nature friendly products. Basalt reinforced composites developed recently, and these mineral amorphous fibres are a valid alternative to carbon fibres for their lower cost and to glass fibres for their strength. The present paper describes briefly on basalt and carbon fibres (uni-directional) which are used as reinforcement materials for composites. The matrix epoxy (LY 556-HY 951) is taken into account to assess its influence on the evaluated parameters. In order to use reinforced composites for structural applications, it is necessary to perform a mechanical characterization. With this aim experiments like tensile strength, flexural strength, hardness and water absorption are performed. Later the mechanical properties obtained from experiments are compared with ANSYS software results.

Keywords: carbon fibre, basalt fibre, uni-directional, reinforcement, mechanical tests, water absorption test, ANSYS

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Authors: Rahul Paul, Kedar Nath Das

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The paradigm of Reinforcement Learning (RL) has become prominent in training intelligent agents to make decisions in environments that are both dynamic and uncertain. The primary objective of RL is to optimize the policy of an agent in order to maximize the cumulative reward it receives throughout a given period. Nevertheless, the process of optimization presents notable difficulties as a result of the inherent trade-off between exploration and exploitation, the presence of extensive state-action spaces, and the intricate nature of the dynamics involved. Evolutionary Optimization Methods (EOMs) have garnered considerable attention as a supplementary approach to tackle these challenges, providing distinct capabilities for optimizing RL policies and value functions. The ongoing advancement of research in both RL and EOMs presents an opportunity for significant advancements in autonomous decision-making systems. The convergence of these two fields has the potential to have a transformative impact on various domains of artificial intelligence (AI) applications. This article highlights the considerable influence of EOMs in enhancing the capabilities of RL. Taking advantage of evolutionary principles enables RL algorithms to effectively traverse extensive action spaces and discover optimal solutions within intricate environments. Moreover, this paper emphasizes the practical implementations of EOMs in the field of RL, specifically in areas such as robotic control, autonomous systems, inventory problems, and multi-agent scenarios. The article highlights the utilization of EOMs in facilitating RL agents to effectively adapt, evolve, and uncover proficient strategies for complex tasks that may pose challenges for conventional RL approaches.

Keywords: machine learning, reinforcement learning, loss function, optimization techniques, evolutionary optimization methods

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Authors: Ghibeche Abderrahmane

Abstract:

To examine whether genes associated with cellular defense against oxidative stress are associated with insulin sensitivity, patients with type 2 diabetes (n=7) and age-matched (n=5) and young (n=9) control subjects underwent a euglycemic-hyperinsulinemic clamp for 120 min. Muscle samples were obtained before and after the clamp and analyzed for heat shock protein (HSP)72 and heme oxygenase (HO)-1 mRNA, intramuscular triglyceride content, and the maximal activities of β-hyroxyacyl-CoA dehydrogenase (β-HAD) and citrate synthase (CS). Basal expression of both HSP72 and HO-1 mRNA were lower (P < 0.05) by 33 and 55%, respectively, when comparing diabetic patients with age-matched and young control subjects, with no differences between the latter groups. Both basal HSP72 (r = 0.75, P < 0.001) and HO-1 (r = 0.50,P < 0.05) mRNA expression correlated with the glucose infusion rate during the clamp. Significant correlations were also observed between HSP72 mRNA and both β-HAD (r = 0.61, P < 0.01) and CS (r = 0.65, P < 0.01). HSP72 mRNA was induced (P < 0.05) by the clamp in all groups. Although HO-1 mRNA was unaffected by the clamp in both the young and age-matched control subjects, it was increased (P < 0.05) ∼70-fold in the diabetic patients after the clamp. These data demonstrate that genes involved in providing cellular protection against oxidative stress are defective in patients with type 2 diabetes and correlate with insulin-stimulated glucose disposal and markers of muscle oxidative capacity. The data provide new evidence that the pathogenesis of type 2 diabetes involves perturbations to the antioxidant defense mechanism within skeletal muscle.

Keywords: euglycemic-hyperinsulinemic, HSP72, mRNA, diabete

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Authors: M. Gangadharappa, M. Ravi Kumar, H. N. Reddappa

Abstract:

The mechanical properties and morphological analysis of Al6061-Red mud particulate composites were investigated. The compositions of the composite include a matrix of Al6061 and the red mud particles of 53-75 micron size as reinforcement ranging from 0% to 12% at an interval of 2%. Stir casting technique was used to fabricate Al6061-Red mud composites. Density measurement, estimation of percentage porosity, tensile properties, fracture toughness, hardness value, impact energy, percentage elongation and percentage reduction in area. Further, the microstructures and SEM examinations were investigated to characterize the composites produced. The result shows that a uniform dispersion of the red mud particles along the grain boundaries of the Al6061 alloy. The tensile strength and hardness values increases with the addition of Red mud particles, but there is a slight decrease in the impact energy values, values of percentage elongation and percentage reduction in area as the reinforcement increases. From these results of investigation, we concluded that the red mud, an industrial waste can be used to enhance the properties of Al6061 alloy for engineering applications.

Keywords: Al6061, red mud, tensile strength, hardness and microstructures

Procedia PDF Downloads 541

Authors: Khosro Ghazvinian, Touba Khodaeian

Abstract:

To improve the oxidative stability of meat products, the use of dietary form of antioxidants can extend the shelf life and acceptability of muscle food during exposition or storage condition. As shown, this method is more effective than adding direct preservatives due to uniform incorporation of dietary additives into sub cellular membrane and therefore, they can properly inhibit the oxidative reaction at their localized sites. Furthermore, postmortem addition of antioxidants to meat cannot directly inhibit the oxidation in membrane phospholipids. Therefore, this study was designed to evaluate the effects of feed supplementation with Melissa officinalis leaves on lipid peroxidation of chicken breast fillets during refrigerated storage. In this study, 72 one-day old Ross 308 broilers distributed in four groups with six replicates (3 chickens each) were fed a basal diet (CONT) or basal diet supplemented with 5, 10, and 15 gr/Kg M.officinalis, for 6 weeks. Following slaughter, fillets from breast were stored at 4 °C in the dark for 12 days, and lipid oxidation was assessed on the basis of thiobarbituric acid reactive substances (TBARS) formed. Results showed that incorporation of M.officinalis in broiler diets delayed lipid oxidation in raw breast meat during refrigerated storage comparative with CONT(p<0.05). In this regard, TBARS levels of breast samples containing higher concentrations (10 and 15 gr/Kg) of M. officinalis (625.43 and 504.32 µg/kg MDA equivalents, respectively )were significantly lower than those of control and 5g/kg samples (872.75 and 841.32 µg/kg MDA equivalents, respectively) (p<0.05). Therefore, M. officinalis might be utilized in novel applications as a nutritional supplement or a functional food component.

Keywords: breast fillet, lipid oxidation, Melissa officinalis, TBARS assay

Procedia PDF Downloads 246

Authors: Moussa Majed, Omar Yaser

Abstract:

The main objective of this experiment was to study the impact of Probiotic compound on the specific immunity as the case study of infectious bursal disease. Total of 8000 one-day old Ross 108 broiler were randomly divided into two experimental groups; control group (4500 birds) and experimental group (3500 birds). Birds in two groups were reared under similar environmental conditions. Birds in control group received basal diets without probiotic whereas the birds in experimental one were fed basal diets supplemented with a commercial probiotic mixture) probiotic lacting k, which contains bacteria cells beyond to lactobacillus, Streptococcus and bifidobacterium genus that are isolated from gut microflora in healthy chickens(. The commercial probiotic were used according to the manufacturer instruction. 400 blood samples for each group were collected from wing vein every 5-7 days as interval period till 42 days old. Indirect Enzyme-Linked Immunosorbent Assay (ELISA) test was performed to detect the level of infectious bursal disease virus (IBDV) antibodies. The results clearly showed that the mean of immune titers was significantly (p= 0.03) higher in trail group than control one. The coefficient of variance percentages were 55% and 39% for control and trial groups respectively, this illustrates that homogeneity of immunity titers in the trail group was much better comparing with control group. The values of geometric means of titers in the control group and trial group were reported 3820 and 8133, respectively. The crude mortality rate in the experimental group was two times lower comparing with control group (14% and 28% respectively, p = 0.005

Keywords: probiotic, broiler chicken, infectious bursal disease, immunity, ELISA test

Procedia PDF Downloads 42

Authors: Mohammad S. Rouhi, Magdalena Juntikka

Abstract:

Processing of polymer fiber composites has a remarkable influence on their mechanical performance. These mechanical properties are even more influenced when using recycled reinforcement. Therefore, we place particular attention on the evaluation of micromechanical models to estimate the mechanical properties and compare them against the experimental results of the manufactured composites. For the manufacturing process, an epoxy matrix and carbon fiber production cut-offs as reinforcing material are incorporated using a vacuum infusion process. In addition, continuous textile reinforcement in combination with the epoxy matrix is used as reference material to evaluate the kick-down in mechanical performance of the recycled composite. The experimental results show less degradation of the composite stiffness compared to the strength properties. Observations from the modeling also show the same trend as the error between the theoretical and experimental results is lower for stiffness comparisons than the strength calculations. Yet still, good mechanical performance for specific applications can be expected from these materials.

Keywords: composite recycling, carbon fibers, mechanical properties, micromechanics

Procedia PDF Downloads 132

Authors: Sandile Daniel Ngidi

Abstract:

Masonry structures often crack due to different factors, which include differential movement of structures, thermal expansion, and seismic waves. Retrofitting is introduced to ensure that these cracks do not expand to a point of making the wall fail. Crack stitching is one of many repairing methods used to repair cracked masonry walls. It is done by stitching helical stainless steel reinforcement bars to reconnect and stabilize the wall. The basic element of this reinforcing system is the mechanical interlink between the helical stainless-steel bar and the grout, which makes it such a flexible and well-known masonry repair system. The objective of this review was to use previous experimental work done by different authors to check the efficiency and effectiveness of using the crack stitching technique to repair and stabilize masonry walls. The technique was found to be effective to rejuvenate the strength of a masonry structure to be stronger than initial strength. Different factors were investigated, which include economic features, sustainability, buildability, and suitability of this technique for application in developing communities.

Keywords: brickforce, crack-stitching, masonry concrete, reinforcement, wall panels

Procedia PDF Downloads 139

Authors: Androniki-Anna Doulgeroglou, Panagiotis Kotronis, Giulio Sciarra, Catherine Bouillon

Abstract:

The interaction diagrams are functions that define ultimate states expressed in terms of generalized forces (axial force, bending moment and shear force). Two characteristic states for reinforced concrete (RC) sections are proposed: the first characteristic state corresponds to the yield of the reinforcement bars and the second to the peak values of the generalized forces generalized displacements curves. 3D numerical simulations are then conducted for RC columns and the global responses are compared to experimental results. Interaction diagrams for combined flexion, shear and axial force loading conditions are numerically produced for symmetrically RC square sections for different reinforcement ratios. Analytical expressions of the interaction diagrams are also proposed, satisfying the condition of convexity. Comparison with interaction diagrams from the Eurocode is finally presented for the study cases.

Keywords: analytical convex expressions, finite element method, interaction diagrams, reinforced concrete

Procedia PDF Downloads 112

Authors: Gloria P. Manu, Johnson K. Efavi, Abu Yaya, Grace K. Arkorful, Frank Godson

Abstract:

Plastics have been used extensively in both food and water packaging and other applications because of their inherent properties of low bulk densities and inertness as well as its low cost. Waste management of these plastics after usage is troubling in Ghana. One way of addressing the environmental problems associated with these plastic wastes is by recycling into useful products such as composites for energy and construction applications using natural or local materials as reinforcement. In this work, composites have been formed from waste low-density polyethylene (LDPE) and kaolin at temperatures as low as 70 ֯C using low-cost solvents like kerosene. Chemical surface modifications have been employed to improve the interfacial bonding resulting in the enhancement of properties of the composites. Kaolin particles of sizes ≤ 90µm were dispersed in the polyethylene matrix. The content of the LDPE was varied between 10, 20, 30, 40, 50, 60, and 70 %wt. Results obtained indicated that all the composites exhibited impressive compressive and flexural strengths with the 50%wt. composition having the highest strength. The hardness value of the composites increased as the polyethylene composition reduces and that of the kaolin increased. The average density and water of absorption of the composites were 530kg/m³ and 1.3% respectively.

Keywords: polyethylene, recycling, waste, composite, kaolin

Procedia PDF Downloads 145